A software development approach where AI agents autonomously plan, write, test, and debug code while the developer maintains architectural control and reviews significant changes.
Vibe coding says “forget the code exists.” Agentic coding says “own the architecture, let the AI handle the typing.”
In agentic coding, an AI agent receives a goal, plans the implementation, writes code across multiple files, runs tests, analyzes failures, and iterates. The developer stays in the architect’s seat, defining constraints, reviewing significant changes, and steering the agent when it drifts. The agent handles volume. The developer handles judgment.
How it works in practice
A developer working with an agentic coding tool might describe a feature at the architectural level: what it should do, how it should integrate with existing systems, what patterns to follow. The AI agent then generates the implementation, runs the test suite, identifies failures, and fixes them, potentially across multiple iterations without developer intervention. The developer reviews the result, provides feedback, and the agent adjusts.
What separates it from vibe coding
The developer’s involvement. In vibe coding, the developer is optional after the initial prompt. In agentic coding, the developer is the decision-maker throughout. They set the standards, review the output, and own the architecture. The AI handles the labor-intensive parts of implementation. The distinction matters because it determines the quality ceiling and the maintainability of what gets built.
Why it matters for technology teams
Agentic coding changes the developer’s role from writer to reviewer and architect. A developer using agentic tools can move faster across a larger codebase because the AI handles routine implementation while the developer focuses on design decisions, system integration, and quality standards. For organizations building custom marketing technology, internal tools, or integrations, that is a meaningful shift in how engineering capacity is used.